Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume.

ABSTRACT:

Objective

Schizophrenia can be divided into deficient schizophrenia (DS) and non-deficient schizophrenia (NDS) according to the presence of primary and persistent negative symptoms. So far, there are few studies that have explored the differences in functional connectivity (FC) between the different subtypes based on the region of interest (ROI) from GMV (Gray matter volume), especially since the characteristics of brain networks are still unknown. This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. Then, the relationships between the alterations and the clinical symptoms were analyzed. In addition, the thalamic functional connection imbalance in the two groups w

SUBMITTER: Zhu W 

PROVIDER: S-EPMC10083255 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature